Chapter 2: Group Consensus



  • What are the key chapter elements (take home messages) that I should test you on?



  • What new things are you curious about and/or did not fully understand



  • What is the coolest thing you learned?

We are on leading edge of the space time continuum

How do you view the timeline of the history of life on Earth?


  • Starts at early life?
    • where is that?


  • Biased towards human existence?


  • What processes are key? Is tempo (time between events) important?


  • Something non-science based?


  • Perspective matters: Understanding the history of biodiversity and critical landmarks in life on Earth help us analyze current changes on Earth

The Earth is old…and it took a while for life to form.



  • Surface was way too hot to start
    • cooled enough to make a solid crust
    • cooled enough sustain liquid water


  • An atmosphere needed to form
    • Without an ozone layer, radiation from sun was too intense
    • Oxygen needed to accumulate for animals


  • Lots of inorganic molecules but no organic molecules
    • early atmosphere was reducing

Miller & Urey experiments

Origin of herdity was key for contempoary life

  • RNA probably came first
    • ~3.8 billion years ago


  • Somewhere between the formation of RNA and cellular life a mechanisms to pass genetic information from partent to offspring emerged (heredity)


  • Heredity is the key for evolution of life and biodiversity
    • replication → variation → competition → natural selection
    • mutations (replication mistakes) are the unit of variation


  • Heredity likely took place in early ‘protocells’ with compartmentalized RNA
    • have not been re-created in the lab

Cellular life begins ~3.5 billion years ago (key events)

Single-celled organisms altered the evolutionary landscape

Why did the Cambrian period explode?

Most groups of organims (still in ocean) evolve around Cambrian

GCB science is interdisciplinary by necessity


GCB embraces diverse perspectives by necessity

Scientific bias in GCB can have vast socio-economic consequences

Targes, investment, policy and consequences do not align

GCB is diverse but utilizes same scientific principles


  • Vast array of methods due to diversity of fields
    • ecology, evolution, conservation, physiology, etc.


  • Data generated is super diverse
    • observational study → genomics → climate modeling


  • Stressors to be studied are many


  • Time frames needed are not the same
  • All these studies utilize the same design principles
    • Independent and dependent variables
    • Treatments and controls
    • Main effects and interactions


  • Studies must have replication
    • modeling or genomics may be exceptions


  • Studies should have randomization

Review and critical thinking of experimental design



Simply define independent and dependent variables


Why is a control treatment absolutely necessary?


Why does replication matter for statistics?


If there is an interaction effect between 2 variables (say warming and drought) are you allowed to talk about a main effect by itself (say warming)?

GCB science varies in approach

  • Observe and record natural systems undergoing change without manipulation
    • tuskless elephants, length of butterfly tongues, etc.


  • Search for mechanisms by manipulation (treatments)
    • field or laboratory
    • focus on key variables


  • Use math and computers to predict
    • use measured trends to project forward with some level of uncertainity
    • species interactions to global climate


  • Combine many single studies to understand if broad patterns exist
    • may ignore unexpected or negative results


  • Use citizen participation to increase scope

GCB science uses the entire cool science toolkit


  • Environmental monitoring must be expansive
    • ocean → atmosphere &#859
    • satellites → lasers → submarines


  • Lots of different organisms to monitor

    • microbes → plants → whales
    • human observation → satellites


  • Biodiversity and species responses are key

    • soil microbiome → adaptation → allele diversity
    • molecular biology tools are vital


  • Many experiments or approached generate large datasets
    • climate monitoring to genomics
    • advanced computing is often necessary


How is GCB data often visualized? Let’s review and practice


  • How could we show a significant relationship between 2 key variables?


  • What is the difference between a linear and exponential function (relationship)?
    • draw a weak exponential relationship between atmopsheric CO2 and ocean pH


  • How could you show the results of an experiment with treatments?


  • Why does both the center and the spread of data matter?
    • draw a comparison of control and warming treatments that are likely biologically different